Comparison of imaging modalities and source-localization algorithms in locating the induced activity during deep brain stimulation of the STN.
Annu Int Conf IEEE Eng Med Biol Soc
; 2016: 105-108, 2016 Aug.
Article
en En
| MEDLINE
| ID: mdl-28268291
One of the most commonly used therapy to treat patients with Parkinson's disease (PD) is deep brain stimulation (DBS) of the subthalamic nucleus (STN). Identifying the most optimal target area for the placement of the DBS electrodes have become one of the intensive research area. In this study, the first aim is to investigate the capabilities of different source-analysis techniques in detecting deep sources located at the sub-cortical level and validating it using the a-priori information about the location of the source, that is, the STN. Secondly, we aim at an investigation of whether EEG or MEG is best suited in mapping the DBS-induced brain activity. To do this, simultaneous EEG and MEG measurement were used to record the DBS-induced electromagnetic potentials and fields. The boundary-element method (BEM) have been used to solve the forward problem. The position of the DBS electrodes was then estimated using the dipole (moving, rotating, and fixed MUSIC), and current-density-reconstruction (CDR) (minimum-norm and sLORETA) approaches. The source-localization results from the dipole approaches demonstrated that the fixed MUSIC algorithm best localizes deep focal sources, whereas the moving dipole detects not only the region of interest but also neighboring regions that are affected by stimulating the STN. The results from the CDR approaches validated the capability of sLORETA in detecting the STN compared to minimum-norm. Moreover, the source-localization results using the EEG modality outperformed that of the MEG by locating the DBS-induced activity in the STN.
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Enfermedad de Parkinson
/
Algoritmos
/
Encéfalo
/
Magnetoencefalografía
/
Estimulación Encefálica Profunda
/
Electroencefalografía
Límite:
Humans
Idioma:
En
Revista:
Annu Int Conf IEEE Eng Med Biol Soc
Año:
2016
Tipo del documento:
Article
Pais de publicación:
Estados Unidos